For all motor vehicles operated on public roadways, taillight signals are a legally required item. The status of the taillight signals can help drivers understand an intention of another driver in a vehicle in front (a leading proximate vehicle). Compared to nighttime driving, even for human drivers, it is more difficult to distinguish the status of the taillight signals of a vehicle during daytime. For an autonomous vehicle control system, it is crucial to identify the status of the taillight signals of a vehicle and thereby determine the intentions of the drivers of other leading vehicles. Additionally, there are limitations in the conventional camera systems in autonomous vehicles, which make it difficult for conventional autonomous vehicle control systems to recognize the status of the taillights of leading vehicles, particularly in daylight conditions. Moreover, it is more complex for autonomous vehicle control systems to distinguish a taillight signal indicating a turning intention than a taillight signal indicating a braking condition. The diversity of vehicle types also poses many challenges, especially considering heavy-duty vehicles. Conventional autonomous vehicle control systems have been unable to implement a taillight recognition capability that replicates a human driver's ability to quickly and accurately recognize taillight signals in a variety of driving conditions. As a result, the safety and efficiency of autonomous vehicle control is being compromised by the inability of conventional systems to implement taillight recognition for determining the intentions of drivers of leading proximate vehicles.